WNTRAC: AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19 Parthasarathy Suryanarayanan1,*, Ching-Huei Tsou1, Ananya Poddar1, Diwakar Mahajan1, Bharath Dandala1, Piyush Madan2, Anshul Agrawal1, Charles Wachira3, Osebe Mogaka Samuel3, Osnat Bar-Shira4, Clifton Kipchirchir3, Sharon Okwako3, William Ogallo3, Fred Otieno3, Timothy Nyota3, Fiona Matu3, Vesna Resende Barros4, Daniel Shats4, Oren Kagan4, Sekou Remy3, Oliver Bent3, Pooja Guhan3, Shilpa Mahatma1, Aisha Walcott-Bryant3, Divya Pathak1, and Michal Rosen-Zvi4 1IBM Research, Yorktown Heights, USA 2IBM Research, Cambridge, USA 3IBM Research, Nairobi, Kenya 4IBM Research, Mount Carmel Haifa, Israel *corresponding author(s): Parthasarathy Suryanarayanan (
[email protected]) ABSTRACT The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human society throughout the world. Against an emerging, highly transmissible disease with no definitive treatment or vaccine, governments worldwide have implemented non-pharmaceutical intervention (NPI) to slow the spread of the virus. Examples of such interventions include community actions (e.g. school closures, restrictions on mass gatherings), individual actions (e.g. mask wearing, self-quarantine), and environmental actions (e.g. public facility cleaning). We present the Worldwide Non-pharmaceutical Interventions Tracker for COVID-19 (WNTRAC), a comprehensive dataset consisting of over 6,000 NPIs implemented worldwide since the start of the pandemic. WNTRAC covers NPIs implemented across 261 countries and territories, and classifies NPI measures into a taxonomy of sixteen NPI types. NPI measures are automatically extracted daily from Wikipedia articles using natural language processing techniques and manually validated to ensure accuracy and veracity. We hope that the dataset is valuable for policymakers, public health leaders, and researchers in modeling and analysis efforts for controlling the spread of COVID-19.